Api Cost Optimizer

Analyze OpenClaw agent configuration and API usage patterns to identify cost-saving opportunities. Diagnose inefficient heartbeat configs, estimate daily/wee...

Diagnose, estimate, and optimize LLM API costs for OpenClaw agents running 24/7.

What This Skill Does

• Estimates API spend from agent configuration (model, heartbeat interval, task complexity)
• Diagnoses heartbeat waste — the #1 cause of runaway API bills
• Counts and categorizes tools the agent has access to
• Produces a cost report with prioritized recommendations
• Estimates time-to-payback for any recommended changes

The Problem This Solves

Documented cases show agents burning $8–$250 per week in API costs due to misconfigured heartbeats and inefficient task patterns. A properly tuned heartbeat alone can reduce costs by 60–90%.

Environment Variables

Variable	Required	Default	Description
API_COST_MODEL	No	openai	Provider: openai, anthropic, minimax, lmstudio
API_COST_INTERVAL	No	weekly	Report interval: daily, weekly, monthly
HEARTBEAT_INTERVAL	No	auto	Override heartbeat interval in seconds (auto-detect if not set)
MODEL_PRICE_INPUT	No	auto	Price per 1M input tokens (auto-selected by provider)
MODEL_PRICE_OUTPUT	No	auto	Price per 1M output tokens (auto-selected by provider)

Provider Default Pricing (per 1M tokens)

Provider	Model	Input	Output
OpenAI	GPT-4o	$2.50	$10.00
OpenAI	GPT-4o-mini	$0.15	$0.60
OpenAI	GPT-4-turbo	$10.00	$30.00
Anthropic	Claude 3.5 Sonnet	$3.00	$15.00
Anthropic	Claude 3 Opus	$15.00	$75.00
MiniMax	MiniMax-M2	$0.10	$0.10
MiniMax	MiniMax-M2.1	$0.20	$0.40

Scripts

analyze.sh — Full Cost Analysis

Runs a complete cost diagnostic on the current OpenClaw configuration.

./scripts/analyze.sh

Output: Detailed markdown report with:

• Estimated API spend (daily / weekly / monthly)
• Heartbeat cost analysis
• Tool count risk factor
• Top 3 cost reduction recommendations
• Estimated savings after optimization

heartbeat_diagnosis.sh — Find Heartbeat Waste

Checks OpenClaw heartbeat configuration and calculates wasted API calls.

./scripts/heartbeat_diagnosis.sh

Output: Heartbeat efficiency score (0–100%), wasted calls per day, estimated annual waste.

estimate.sh — Quick Cost Estimate

One-shot estimate with optional custom parameters.

./scripts/estimate.sh <heartbeat_seconds> <tasks_per_day> <avg_input_tokens> <avg_output_tokens>

Output: Daily, weekly, and monthly cost estimates for the given parameters.

Cost Reduction Recommendations

Priority order:

1. Increase heartbeat interval — If heartbeat is under 5 minutes, increase to 10–30 min for idle agents
2. Switch to cheaper model — MiniMax M2 at $0.10/1M is 25x cheaper than GPT-4o for most tasks
3. Batch tasks — Run 5–10 tasks per session instead of 1 task per heartbeat cycle
4. Cache responses — Use memory skills to avoid repeated context
5. Disable verbose logging — Reduces token churn in long conversations

Usage Example

# Full analysis with MiniMax pricing
export API_COST_MODEL=minimax
./scripts/analyze.sh

# Quick estimate
./scripts/estimate.sh 300 20 8000 2000

# Heartbeat-only diagnosis
./scripts/heartbeat_diagnosis.sh

Notes

• Estimates are based on configuration analysis, not live API metering
• For actual spend tracking, enable provider cost logs and compare
• MiniMax models offer best price/performance for volume workloads
• Heartbeat waste is typically the single largest cost lever